Update app.py

app.py

@@ -1,18 +1,8 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 import json
-import uuid
-from PIL import Image
 from bs4 import BeautifulSoup
 import requests
-import random
-from transformers import LlavaProcessor, LlavaForConditionalGeneration, TextIteratorStreamer
-from threading import Thread
-import re
-import time 
-import torch
-import cv2
-from gradio_client import Client, file
 
 def extract_text_from_webpage(html_content):
     soup = BeautifulSoup(html_content, 'html.parser')
@@ -22,13 +12,12 @@ def extract_text_from_webpage(html_content):
 
 def search(query):
     term = query
-    start = 0
     all_results = []
     max_chars_per_page = 8000
     with requests.Session() as session:
         resp = session.get(
             url="https://www.google.com/search",
-            headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"},
+            headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36"},
             params={"q": term, "num": 3, "udm": 14},
             timeout=5,
             verify=None,
@@ -40,7 +29,7 @@ def search(query):
             link = result.find("a", href=True)
             link = link["href"]
             try:
-                webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"}, timeout=5, verify=False)
+                webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36"}, timeout=5, verify=False)
                 webpage.raise_for_status()
                 visible_text = extract_text_from_webpage(webpage.text)
                 if len(visible_text) > max_chars_per_page:
@@ -50,9 +39,7 @@ def search(query):
                 all_results.append({"link": link, "text": None})
     return all_results
 
-# Initialize inference clients for different models
 client_gemma = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
-client_mixtral = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO")
 client_llama = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
 
 func_caller = []
@@ -93,7 +80,7 @@ def respond(message, history):
             web_results = search(query)
             gr.Info("Extracting relevant Info")
             web2 = ' '.join([f"Link: {res['link']}\nText: {res['text']}\n\n" for res in web_results if res['text']])
-            messages = f"system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You are provided with WEB results from which you can find informations to answer users query in Structured and More better way. You do not say Unnecesarry things Only say thing which is important and relevant. You also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions."
+            messages = f"Web Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
             for msg in history:
                 messages += f"\nuser\n{str(msg[0])}"
                 messages += f"\nassistant\n{str(msg[1])}"
@@ -105,7 +92,7 @@ def respond(message, history):
                     output += response.token.text
                     yield output
         else:
-            messages = f"system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions."
+            messages = f"Web Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
             for msg in history:
                 messages += f"\nuser\n{str(msg[0])}"
                 messages += f"\nassistant\n{str(msg[1])}"
@@ -117,7 +104,7 @@ def respond(message, history):
                     output += response.token.text
                     yield output
     except:
-        messages = f"system\nYou are OpenCHAT mini a helpful assistant made by KingNish. You answers users query like human friend. You are also Expert in every field and also learn and try to answer from contexts related to previous question. Try your best to give best response possible to user. You also try to show emotions using Emojis and reply like human, use short forms, friendly tone and emotions."
+        messages = f"Web Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
         for msg in history:
             messages += f"\nuser\n{str(msg[0])}"
             messages += f"\nassistant\n{str(msg[1])}"
@@ -133,8 +120,8 @@ demo = gr.ChatInterface(
     fn=respond,
     chatbot=gr.Chatbot(show_copy_button=True, likeable=True, layout="panel"),
     description=" ",
-    textbox=gr.MultimodalTextbox(),
-    multimodal=True,
+    textbox=gr.Textbox(), 
+    multimodal=False, 
     concurrency_limit=200,
 )
 demo.launch()